Wood tracking by identification of surface characteristics

ABSTRACT

A “woodprint™” characterization and identification technique unique employs cameras ( 16 ), lighting ( 14 ), camera interface hardware ( 18 ), a computer ( 20 ), and/or image processing software to collect and analyze surface characteristics of pieces of wood ( 8 ) to track them through an automated production process in real-time with information that is specific to each wood piece ( 8 ), such as what machining is required, its value, and/or its destination. When a wood piece ( 8 ) reaches a point in the production process where a decision is required, its unique identity is used to retrieve appropriate information previously determined and assigned to the wood piece ( 8 ).

RELATED APPLICATIONS

This patent application derives priority from U.S. ProvisionalApplication No. 60/489,862, filed Jul. 24, 2003.

COPYRIGHT NOTICE

© 2004 Lucidyne Technologies, Inc. A portion of the disclosure of thispatent document contains material that is subject to copyrightprotection. The copyright owner has no objection to the facsimilereproduction by anyone of the patent document or the patent disclosure,as it appears in the Patent and Trademark Office patent file or records,but otherwise reserves all copyright rights whatsoever. 37 CFR § 1.71(d).

TECHNICAL FIELD

The present invention relates generally to lumber or board tracking and,more particularly, to using unique surface characteristics(“woodprints”) for identifying individual pieces of wood and trackingthem through an automated production process with real-time informationspecific to the pieces or wood such that when a board or other piece ofwood reaches a machining operation or decision point, its predeterminedcharacteristic information, such as processing information, value, ordestination, can be automatically retrieved to influence how such pieceof wood is handled.

BACKGROUND OF THE INVENTION

Conventional board tracking devices rely on spraying or imprinting anidentification code or symbol on each board and reading the informationwith a sensor after the board has traveled to a subsequent machiningstation. The printing and reading processes are preferably performed athigh speeds and may be physically difficult to reliably achieve becauseof the dynamic nature of the boards themselves.

If wood is missing from an area where the board is printed, the board'sidentification code can be illegible to the reader. A twisted board, orone with bark or some other defect in the print zone, can also bedifficult to reliably mark and identify. A board may also turn overduring travel between stations, requiring that either both sides bemarked, or both sides be read.

Another problem with conventional board tracking devices is thatprinting systems contain print media, such as ink or paint, and movingparts that contribute to decreasing reliability. Ink jet and/or spraysystems require constant maintenance to keep them working properly. Mostrequire compressed air, are adversely affected by temperature extremes,and are very sensitive to variations in the ink or paint quality. Forexample, unless the print media is continually circulated when thesystem is not in use, the print media can freeze, its pigments canseparate, and print nozzles can become plugged. The required maintenancecan cost thousands of dollars annually beyond the cost of replacementparts and the original equipment itself. When a marking system fails,the failure is typically not detected until the boards reach the nextmachine center, potentially meaning that a hundred or more boards mustbe physically removed from the process and either reintroduced ahead ofthe marking system or manually processed.

Marking boards with ink or paint can reduce their value as potentialappearance-grade products destined for exposed applications. Boardstypically processed through a marking system have been previously planedand are ready for immediate use. Some uses include wall paneling orexposed ceilings and floors. If the final finish will be a non-opaquestain or paint, any non-natural marking will not be acceptable.Furthermore, print media typically contain or are mixed with afluorescent pigment or dye to provide better contrast to improvemark-reading performance. Such pigments may be invisible in normallighting, but the marks will glow under an ultraviolet (black light)source. The ultraviolet marks are, therefore, unacceptable forapplications where the surfaces are inadvertently illuminated by alighting source that emits UV light.

While existing board tracking systems may be suitable for some specificpurposes, a more universal method for tracking boards, regardless oftheir condition or their final application, is desirable.

SUMMARY OF THE INVENTION

An object of the present invention is, therefore, to provide an improvedwood tracking system.

Another object of the invention is to provide a surface “woodprinting™”system and/or method for tracking pieces of wood.

An alternative object of the invention is to employ such woodprinting™capabilities to identify individual pieces of wood using their uniqueinherent surface characteristics in order to track the wood in real-timethrough an automated production process.

Another alternative object of the invention is to provide woodprinting™capabilities that identify each piece of wood by its unique graincharacteristics.

A further alternative object of the invention is to providewoodprinting™ capabilities that do not mark or modify the wood surfaceor its appearance.

Yet another alternative object of the invention is to providewoodprinting™ capabilities that can be used on any face, edge, and/orend of surfaced or unsurfaced wood of any moisture content.

Still another alternative object of the invention is to providewoodprinting™ capabilities that are relatively insensitive to lightingor positioning differences during image data collection.

As with human fingerprints and snowflakes, wood cells in trees developin distinct manners as a result of many factors, including genetics,environment, weather, soil, local life form effects, and many othercontributing elements. The surface of an individual board or piece ofwood can also be cut from a tree in an infinite number of angles.Accordingly, the resulting exposed grain structure of any given surfacewill be unique when compared to that of any other surface of any otherpiece of wood. Even boards taken from the same tree and cut at similarangles will have unique grain structures. Furthermore, if the piece ofwood is twisted, has some bark, is missing wood, has other physicalshape defects such as wane defects, or has other defects such as knotsor pitch, within an area of interest, these features become additionalcharacteristics that can be used to uniquely identify the piece of wood.

Some embodiments provide a surface “boardprint™” or “woodprint™”identification technique for identifying individual pieces of wood usingtheir inherent unique surface characteristics to track them in real timethrough an automated production process. Such embodiments overcome manyof the disadvantages of conventional board tracking devices. Theimproved tracking technique permits information specific to a piece ofwood, such as proposed machining information, value, destination, and/orother characteristics, to follow the individual piece of wood through anautomated process. Thus, when the piece of wood reaches a point in aproduction process where a decision is desired, the unique identity ofthe wood piece can be used to retrieve the appropriate informationalready associated with it.

Some embodiments employ cameras, lighting, image acquisition hardware, acomputer, and image processing software. Preferred processing algorithmsreduce effects from random or varying angles of image collection and/orfrom fluctuations of lighting sources. Statistical parameters,conceptually similar to those used for human fingerprint matchingtechnology, provide a certain amount of flexibility in the analyticalprocess. So, as long as a piece of wood meets desired statisticalrequirements for a match, the wood piece is considered to be a match. Anadjustable tolerance for accuracy can be employed to compensate forfluctuations in the readability of wood grain characteristics, forexample. These techniques are unlike conventional wood trackingtechniques that attempt to find an exact match for a printed code.

Preferred image processing techniques of the invention can be used onany face, edge, and/or end of surfaced or unsurfaced wood of anymoisture content, such as green (uncured) or dry wood, and the imageprocessing techniques are relatively insensitive to defects on thesurfaces. So, unlike convention tracking systems which cannot trackrelatively green or unsurfaced boards that do not facilitate the use ofprint media, embodiments of a woodprint™ identification system can beused anywhere in a sawmill and/or planer mill process where a woodsurface can be imaged and is not limited to use with dry, surfacedboards. Furthermore, since printing or stamping the boards can beeliminated and the image acquisition sensors do not need to contact thewood surfaces, the wood is left with no additional markings that coulddegrade its appearance or adversely affect its value or merchantability.

Preferred embodiments of the invention can be employed to work inconjunction with an automated wood grading system. Because the scanningand computer processing associated with automated board or lumbergrading may take several seconds, boards may travel away from thescanner and be mixed in with subsequent or previous boards withoutadversely affecting throughput. The woodprint™ identification techniquestherefore facilitate automated matching of grade solutions with correctboards or other pieces of wood when they are presented later for furthermachining.

Some preferred embodiments can be implemented without adding appreciablyto the production cost of wood products. Some preferred embodimentsemploy no moving parts and utilize components that are easily protectedfrom temperature fluctuation and other environmental concerns. Somepreferred embodiments can also utilize existing scanning hardware forinitial image acquisition in existing systems, merely adding a softwareelement to the scanning system. Off-the -shelf lighting, cameras, and/orother sensing hardware can be added downstream at various points in theautomated production system. The expected maintenance, such as keepingthe camera viewing ports free from debris, and occasionally replacing oflight sources, would also be minimal. Accordingly, the preferred surfacewoodprinting™ techniques for tracking wood pieces is highly reliable.

Additional objects and advantages of this invention will be apparentfrom the following detailed description of preferred embodiments, whichproceeds with reference to the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a pictorial representation of exemplary desirable componentsof one embodiment of a wood tracking system.

FIG. 2 is a flow diagram of an overview of exemplary wood trackingevents that occur in one embodiment of a wood tracking system.

FIG. 3 is a flow diagram detailing exemplary image analysis executed atan exemplary characterization station in one embodiment of a woodtracking system.

FIG. 4 is a flow diagram detailing exemplary image analysis executed atan exemplary identification station in one embodiment of a wood trackingsystem.

DETAILED DESCRIPTION OF PREFERRED EMBODIMENTS

FIG. 1 shows an exemplary wood tracking system 10 for characterizing andidentifying pieces of wood 8 in a production line as they move in adirection of travel 6 through an automated production process todownstream processing centers and/or sorting bins. FIGS. 2-4 showgeneral and specific flow diagrams of wood tracking events and analysisemployed in some embodiments of wood tracking system 10.

With reference to FIG. 1, a characterization station 12 captures andprocesses an image of at least a portion of each piece of wood 8 andthen coordinates the tracking of the specific pieces of wood 8 with theautomated processing system (APS) as they travel to common or differentmachining centers for the sawing, grading, and/or subsequent sorting.The pieces of wood 8 can flip over during travel or arrive at themachining centers out of sequence. A downstream identification station42 at one or more of such machining centers eventually captures andprocesses the images of most, if not all, the pieces of wood 8. Thenimage data obtained at the identification station 42 is compared toimage data obtained at the station 12 to identify each piece of wood 8and report its location to the automated processing system. Each pieceof wood 8 is then processed or sorted according to wood piece-specificinstructions from the automated process system. After being processed,each piece of wood 8 may be re-characterized by the originalcharacterization station 12 or another characterization station 12 thatis downstream of such processing or machining center.

General embodiments of a wood tracking system 10 include one or morewood characterization stations 12 having one or more light sources 14 aand 14 b (generically light sources 14) and corresponding imageacquisition hardware 16 a and 16 b (generically image acquisitionhardware 16) that are directly or indirectly in communication withcamera interface hardware 18 that is in turn directly or indirectly incommunication with a computer 20. A typical wood characterizationstation 12 also preferably employs image processing software 22 havingcustomized image processing algorithms designed to analyze video, frame,or other captured image information using various data manipulationtechniques described later in detail.

Enough unique inherent information can be extracted from a small surfaceportion of each piece of wood 8 as it travels at a high speed throughthe characterization station 12 to successfully characterize each pieceof wood 8 uniquely. Typically, pieces of wood 8 travel (with their majoraxis in the direction of travel 6 (lineally)) through station 12 atspeeds of about 91 to 910 meters (300 to 3000 feet) per minute and moretypically at speeds of at least 366 meters (1200 feet) per minute andless than about 610 meters (2000 feet) per minute. In some embodiments,a roughly 61-centimeter (two-foot) surface portion that is about onemeter (three feet) from the end of each piece of wood 8 is imaged atstation 12.

For convenience, the terms “wood,” “pieces of wood,” or “wood pieces”may refer to pieces of timber, lumber, logs, flitches, cants, beams,posts, studs, boards, veneer, and/or any other pieces of wood smallerthan the whole tree and larger than sawdust. The surfaces characterizedmay be one or more faces 30, sides 32, and/or ends 34 of the wood pieces8. Skilled persons will appreciate that curved or intersecting surfacesmay additionally or alternatively be characterized at station 12.Skilled persons will appreciate that the minimum area that is imagedshould be an amount of area sufficient to yield a unique recognizablevector file or image packet as later described. Skilled persons willfurther appreciate that the minimum area imaged may be different fordifferent wood products or may be different for wood pieces havingdifferent shapes or sizes. Alternatively, any additional amount of anywood surface can be imaged, including up to all portions of allsurfaces. Skilled persons will also note that any combination ofsurfaces may also be imaged.

In some embodiments, the image captured comprises a high contrast imageof grain and/or growth ring characteristics of a portion of each pieceof wood 8. These features are relatively insensitive to differences inlighting, position, and contrast, but other wood characteristics such astracheid patterns and/or wood defects could be used for identificationpurposes. Such defects might include, but are not limited to, physicalshape defects such as cups, crooks, cracks, knots, wane, twists, bark,and/or pitch.

Although only a portion of one surface of each piece of wood 8 may becharacterized at the characterization station 12, images of portions ofopposite surfaces may also be collected at the characterization station12 so that opposite surface information is available in the event that apiece of wood 8 is turned over in transit between the characterizationstation 12 and the identification station 42. Accordingly, the imageacquisition hardware 16 and the respective lighting sources 14 may bemounted in such a way as to obtain images of portions of opposingsurfaces of each piece of wood 8 as it travels through station 12.

Appropriate gaps may be provided between conveyor belts or other woodconveying means to permit viewing of the bottom surface of each piece ofwood 8. In alternative embodiments, the sets of image acquisitionhardware 16 and light sources 14 may be symmetrically positioned aboutopposite surfaces of wood pieces 8 to characterize opposite surfacessimultaneously or may be positioned at a distance so that the oppositesurfaces are characterized sequentially. Alternatively, pieces of wood 8may intentionally be flipped over and resent through a station 12 havingonly a single set of lighting sources 14 and image acquisition hardware16 to characterize an opposite surface, or the image acquisitionhardware 16 could be moved such that its field of view changed toinclude the opposite surface. However, such embodiments might entailadditional safeguards to ensure that images of the opposite surfaces areproperly correlated with each other. The images or image data collectedat station 12 from some or all of the surfaces may be communicated tothe same computer 20 for processing.

In one embodiment, process blocks 110 a and 110 b employ imageacquisition hardware 16 that comprises one or more monochrome arraycameras with at least about a 1024×768 pixel addressability. Suchcamera(s) can be configured to be electronically shuttered up to atabout at least 7.5 frames/second with an adjustable integration time toinclude 500 microseconds, or such camera(s) can be configured to workwith a strobed light source 14 having similar strobe frequencies. In anexemplary embodiment, a camera is positioned a minimum of 61 centimeters(24 inches) over a face 30 of a target piece of wood 8 to provide aminimum field of view of 36 centimeters by 61 centimeters (14 inches by24 inches) using a fixed lens. Skilled persons will appreciate that thecamera speed and resolution can vary depending on the speed of theproduction line and the maximum field of view desired.

One or more filters (not shown) may be added to reduce or eliminateinfra-red energy and all visible wavelengths except green because mostwood features of interest provide better visible contrast in greenwavelengths. One or more filters may also be added to reduce oreliminate other unwanted characteristics of ambient lighting to enhancedesirable effects of the light source(s) 14. The image acquisitionhardware 16, and/or any other sensitive components as appropriate, maybe housed in a NEMA 12/13-rated enclosure to protect it from temperatureextremes, dust, and dirt. All of the components described above arecommercially available.

In an alternative embodiment in which the wood piece 8 is a board, aSony™ XCD-X700 color camera is mounted about 1.5 meters (five feet)above the face 30 of the board and is preferably oriented substantiallyperpendicularly to the board. The camera is installed in a NEMA12/13-rated enclosure. The camera has a Fire Wire serial communicationport, and a Fire Wire extender converts the Fire Wire signal topropagate through a fiber optic medium over a longer distance than thecamera's own circuitry permits. Only the green color channel from thecamera is used, and the background behind the board is preferably darkto facilitate image collection. The image acquisition cycle is triggeredby a photoeye proximity transition sensor that detects the end 34 oredge 32 of the board, depending on the orientation of the board as ittravels through station 12. Software running in the camera automaticallytransmits the acquired data to a personal computer 20.

In another embodiment, one or more color high-speed line scan cameras,having separate red, blue, and green channels, capture an image from asurface as a piece of wood 8 moves through station 12. The image datafrom the green channel is pieced back together to create an array imagefor subsequent analysis with software tools. In another embodiment, asingle 768×768 pixel monochrome camera is employed to capture an imageof an end 34 of a piece of wood 8 in a field of view of approximately 36centimeters by 36 centimeters (14 inches by 14 inches) at the firststation 12. It is desirable to capture a high quality image, but theparticular method of image data capture employed may not be particularlyrelevant. Skilled persons will appreciate that successful imagecollection is not limited to using imaging techniques described aboveand that numerous types of image acquisition hardware are commerciallyavailable and numerous configurations and positions could be employed.For example, other color or black and white image data may be obtained,or even radio or other frequency data may be obtained and used for“image matching.”

Skilled persons will appreciate that image acquisition hardware may takeon many other forms. In one embodiment, photodiodes are employed tocapture inherent characteristic information obtained from exposing thewood pieces 8 to x-ray radiation. In another embodiment, antennas areemployed to capture inherent characteristic information obtained fromexposing the pieces of wood 8 to radio waves.

Light sources 14 may employ almost any commercially available lightingequipment or known lighting technique. Desirable light sources 14provide wavelengths generally considered to be green light at sufficientenergy to accommodate the integration time necessary to capturewell-contrasted images. Too much light is not likely to be a problemsince the camera aperture or integration time can be adjusted tocompensate for excess intensity. Although light sources 14 withreflector and lens systems that project a visible intensity pattern ontoa wood surface can be employed, lighting embodiments that do not projectvisible intensity pattern onto a wood surface are generally easier toimplement. In one embodiment, station 12 employs one or more abroad-spectrum lamps, such as commercially available halogen or Xenonlamps that consume about 1000 Watts of direct current (DC) power togenerate approximately 800 Watts of light energy. The lamp'sself-contained lens and reflector cast a diffuse light over anapproximate area of about 76 centimeters by 76 centimeters (30 inches by30 inches). The visible energy produced by such a light source 14 is“white,” including energy in green wavelengths that is in proportion tothe energy in other visible wavelengths.

In another embodiment where the wood piece 8 is a board, two 1000 Wattbroad spectrum stage lights are mounted about 1.8 meters (six feet) awayfrom the face 30 of the board at 40 degree angle off the axisperpendicular to the face 30 of the board to reduce reflections andprovide a fairly uniform illumination over a 0.6 meters square (two footsquare) area of the board face 30.

Skilled persons will appreciate that different lighting techniques canbe employed to accommodate different image acquisition hardware 16. If aline scan camera is employed, the light source 14 should be brightenough in the green portion of the visible spectrum, for example, toprovide for successful image integration. In another example, a strobelight source 14 is employed to control the camera's acquisition of theimage instead of depending entirely on a camera's electronic shuttermode. Such light source should also generate sufficient light in thegreen wavelengths of the visible spectrum to acquire a successful imagefor processing. Skilled persons will appreciate that green laser orother coherent light sources 14 can be employed and may be preferredwhen the costs of such embodiments become comparable to the costs ofmore typical light sources such as those discussed above.

Process blocks 112 a and 112 b may employ camera interface hardware 18that preferably resides in a computer 20 and may be a circuit board orcard that captures the resulting image from the image acquisitionhardware 16 for analysis in the computer 20 and that may also controlactivation of image data acquisition and/or strobe light timing. Such acircuit board is often referred to as a “frame grabber,” is commerciallyavailable, and may be located in the computer's system bus. Preferredfunctions of such card include the capability to properly exercisereal-time imaging functions of the image acquisition hardware 16,capture the resulting image data, and present the data to the computer20 for analysis. For some embodiments, such a card is preferably capableof receiving an external signal to initiate each image capture, and thentriggering the strobe and camera to initiate image capture.

Skilled persons will appreciate that if a different kind of camera isused, the camera interface hardware 18 will be changed appropriately.For example, if the image acquisition hardware 16 were a line scandevice, then the camera interface hardware 18 would collect image datain single scanned lines and present the data to the computer 20 forassembly into an array image for evaluation. Skilled persons will alsoappreciate that such card may facilitate only the data collectionprocess and not control the camera. Another example can use a cameracontaining its own acquisition software and hardware, whereby the datais subsequently transmitted to the computer 20 via a serialcommunication link such as USB or Fire Wire, requiring no specialhardware to be installed in the computer 20.

Skilled persons will appreciate that camera interface hardware 18 mayreside in image acquisition hardware 16 or in the personal computer ormay be an independent device that is directly or indirectly interfacedto the image acquisition hardware 16 and/or the computer 20. As camerasand computers 20 are continuing to evolve and take on a more completeroles to ease integration, many or all of the functions camera interfacehardware 18 will be incorporated into the image acquisition hardware 16,such that a high-speed communication port in the computer's motherboardwill accept the data directly from the image acquisition hardware 16 soseparate camera interface hardware 18 may be omitted entirely.

In some embodiments, computer 20 may be an off-the-shelf personalcomputer (PC) with commercially available hardware and softwarecomponents. Such a computer 20 may have typical attributes, such as aprocessor speed of 2 to 3 gigahertz, minimum RAM memory 512 megabytes,hard disk, CD drive, keyboard (kbd), mouse, color monitor, Ethernetnetwork card, Microsoft Windows operating system, an interface hardwarecard, and commercially available and/or customized image processingsoftware and other application(s).

In accordance with process block 114 a, the computer 20 processes theimage data collected from the image acquisition hardware 16 associatedwith station 12, and in accordance with process blocks 116 and 118 thencommunicates the results via an Ethernet connection to other stations42, production line equipment, an automated processing system (APS),and/or possibly other computers. The connections between the variouscomponents and stations can take on many forms, the most common beingcoaxial cable or shielded twisted paired cables. In addition, thecommunication medium could be via fiber optic (light energy) or radiofrequency. The types of connections used may depend on the proposedcommunication method desired and the ability to integrate withpreexisting components of older wood processing systems, and numerousspecific embodiments could be implemented.

The computer hardware employed is expected to be changed over time toincorporate higher speed components and interface devices, as well asincreased memory capacity when appropriate as improved components becomeavailable. For example, an Ethernet 100/10 Base T network can bereplaced by a Gigabit Network or other serial or parallel networks.These communication interfaces can also be integrated into thecomputer's motherboard, eliminating the need for adding a separate cardfor the communication function. Fiber optic or radio frequency mediumsare also potential methods for this function. The computer 20 isconnected to a power source that is preferably protected from voltage orcurrent fluctuations. The image acquisition hardware 16 and lightsources 14 may be connected to the same power source as the computer 20or may be connected to separate power sources.

With the same or different sensors and image processing equipment, theautomated processing system examines each piece of wood 8 to determinethe most beneficial use of each piece of wood 8, such as grade anddimension, and to provide the corresponding processing instructions,such as where to cut. Such examination may be accomplished concurrentlywith characterization for identification, or such examination may occurbefore or after ID characterization or at a separate location.Conventional automated processing systems may employ some or all of thetechniques disclosed in any one of U.S. Pat. Nos. 6,757,058; 6,756,789;5,703,960; 5,644,392; 5,524,771; 5,412,220; 5,254,859; 5,252,836;4,992,949; 4,926,350; 4,916,629; 4,879,752; 4,867,213; 4,831,545;4,827,142; 4,606, 654; 4,301,373; 4,286,880; 4,221,974; 4,207,472;4,086,496; or combinations thereof. The scanning and analyticaltechniques disclosed in these patents are herein incorporated byreference.

With reference again to FIGS. 1-4, an identification station 42 that islater or downstream of the characterization station 12 may employ typesand embodiments of light source(s) 14, image acquisition hardware 16,camera interface hardware 18, and/or computer(s) 20 that are identicalto, or different from, those employed in the previous station 12.Skilled persons will appreciate that in most cases identical types andembodiments of these components are preferred to facilitate ease inmatching the image data of wood surface characteristics obtained atstations 12 and 42.

An image may be captured of an entire surface or from only a specificarea on the piece of wood 8 at both stations 12 and 42, and/oridentification station 42 may capture fewer and/or smaller images ofportions of wood pieces 8 than those captured at the characterizationstation 12. Skilled persons will appreciate that if station 12 obtainsimage data from both of the opposite surfaces of each piece of wood 8,then station 42 will preferably obtain image data from only one of theopposite surfaces in order to establish a match. In some embodiments,pieces of wood travel through station 42 in an intentionally differentorientation than the orientation in which they travel through station12. For example, instead of lineal travel through stations 12 and 42,pieces of wood 8 may have their major axis oriented transversely to, andpreferably perpendicularly to, direction of travel 6 at one or bothstations 12 and 42. Skilled persons will also appreciate that transversetravel speeds may be different from lineal travel speeds.

Preferred embodiments employ a computer 20 at each downstreamidentification station 42. Each computer 20 is preferably capable ofperforming the same tasks concerning collecting image data of woodsurface characteristics from its respective image acquisition hardware,with either computer 20 being able to make the final comparisondecision. Alternatively, downstream computers 20 may be adapted toperform only some or all of the image characterization, but leave thecomparison processing to a central computer (not shown) or a computer 20at a previous station. The computers 20 preferably communicate with eachother and the automated processing system via an Ethernet or otherhigh-speed communication network such as those described above.

Skilled person will appreciate that a single high-speed computer 20 mayperform the image characterization and comparison tasks associated withtwo or more stations 12 and 42. Such a computer 20 would preferablycontain the camera interface hardware for the image acquisition hardwareof each station 12 and 42 and would be configured to multitask betweenthe demands of each. Some pre-existing wood processing systems alreadyhave, for example, a complete scanning system in place that includes itsown light sources 14, cameras, and computers 20 with a softwarearchitecture that facilitates image acquisition in one computer, imageprocessing in another, decision logic in a third, and communication tothe production equipment in another. Skilled persons will alsoappreciate that the image data collection, processing, and decisionprocess can be implemented in multiple computers 20 that are remote fromthe stations 12 or 42 where the image acquisition hardware is located.Skilled persons will further appreciate that station 42 may be at aremote location from station 12 such as a separate milling site orcustomer plant with data sent over the internet or other means, andstation 42 may be operated shortly after or at a much later time fromwhen station 12 acquires the image data of a wood piece 8. The physicallocation and configurations of the data collection and processinghardware can be varied greatly so long as such implementations arereliable and facilitate and desirable processing and communication tasksand speeds.

When a computer 20 receives an image from the image acquisition hardware16, the image and/or data associated with it may be stored in a circularbuffer by software running in the computer 20 at least until the imagedata is received and/or acknowledged by the respective decisions block120 a or 120 b of the image processing hardware. Customized imageprocessing algorithms may be employed to analyze image data with variousdata manipulation techniques. Such software is preferably adapted tooperate in the Windows™ environment and integrate with communicationapplications in order to share data and results with other computers 20.The software is preferably adapted to take advantage of Intel's ImageProcessing Library (IPL), Integrated Performance Primitives (IPP),and/or other available libraries that feature specialized softwareroutines that take advantage of specific processing hardware of thecomputer 20. One advantage of using these libraries is speed. A functioncall to an IPL routine typically runs much faster than improviseddedicated C++ code. In one embodiment where the wood pieces 8 areboards, the image processing software includes C++ libraries and/orVisual Basic® OCX/DLL software provided by a company called ImagingControl of Charlotte, N.C. Another software application resident in thecomputer 20 moves the image out of the buffer to a separate memorylocation so it can be easily accessed by the image processing software.

The software is preferably adapted to perform one or more of thefollowing applications, more preferably two or more of theseapplications, and most preferably all of these applications: imagewarping; Fast Fourier Transformation and/or other transformationtechniques such as wavelet analysis; interim solution communication;woodprint matching; and/or final solution communication. A descriptionof each of these applications is described below.

With reference to process blocks 114 a and 114 b, image warpingaddresses differences between the images taken by the image acquisitionhardware 16 at each station 12 or 42. Such differences include, but arenot limited to: the position of where each piece of wood 8 ends up inthe field of view; resolution differences between the individual imageacquisition hardware 16 at different stations 12 and 42; and imagecontrast. The software will take the image received from the imageacquisition hardware 16 and scale it to correspond to a predeterminedpixel/inch value in accordance with process blocks 124 a and 124 b. Thesoftware will also adjust the orientation of the piece of wood's imageto compensate for any skewing or offset in accordance with processblocks 122 a and 122 b. The scaling and orientation adjustments can bedone in either order. A calibration procedure at installation using atarget with known size and orientation defines the reference points andadjusts for differences in focus, pixel size, lighting, and skew using acalibration target with known size, orientation, and/or other features.

In an exemplary system, where the images taken at stations 12 and 42 areadapted to be appear as similar as possible, the focus, illumination,and spatial alignment are precisely adjusted. Such calibration can beentirely manual or can be partially automated. In an exemplarycalibration process for such a system where the piece of wood 8 is aboard, after the camera and light sources are mounted, a calibrationtarget is placed under the camera. This target may be a board with linesdrawn on it using a green or black marker that border a region ofinterest. The camera is placed in a mode that makes it continuallyacquire images. The focus, aperture, and speed (acquisition time) areadjusted to produce a clear image. The position of the camera is thenmanually adjusted at both stations 12 and 42 so that the cameras producenearly identical images. Focus is readjusted as needed.

In an exemplary image warping application that addresses scaling whereinthe wood piece 8 is a board, the computer software thresholds multiple(or each) horizontal video lines across the image to find the edges ofsides 32 of the board. The data from the longest lines (representing thewidest part of the board) are used in a least-squares fit calculation tocreate an artificial border that represents the edges of the board.Using the longest lines helps eliminate areas of missing wood and darkfiber that can make the board appear narrow. The calculation results ina border rectangle that corresponds to the edges of the board and theportion of the field of view that was calibrated for both stations 12and 42. The image is then scaled to a size compatible to both stations12 and 42 using a bi-linear transformation. The area within the borderrectangle is next divided into two grids: a fine grid and a coarse grid.In an example employing a 25.4-cm (ten-inch) wide board, the fine gridcomprises 100 rectangles or cells and the coarse grid comprises 25rectangles or cells. In some embodiments, each fine cell may, forexample, represent a 64×64 camera pixel area.

In an exemplary image analysis process, each cell may be represented bya set of values determined by a Fast Fourier Transform algorithm inaccordance with process blocks 126 a and 126 b. Exemplary values ofinterest include the most often found frequency in a grain pattern orgrowth ring pattern, a representation of such frequency's energy orabundance (magnitude of predominant spatial frequency) compared to thoseof any other frequencies, and an indication of the grain directionand/or grain direction confidence. Other inherent wood characteristicsthat may be evaluated include, but are not limited to, contrast, density(as obtained by radio wave or x-ray analysis), or wane characteristics.

Values describing two or more of these features are determined for eachcell within both the fine and course grids of the image. Two currentlypreferred values are grain direction and magnitude of its spatialfrequency because these values tend to be fairly insensitive to lightintensity and contrast. The actual numbers resulting from thetransformation may then be thresholded dynamically to compensate forbrightness differences between stations 12 and 42, if desirable. In oneexample, both grain direction and predominant spatial frequency areallocated numbers between 0 and 255. The collection of the resultingnumbers for some or all of the cells for each piece of wood 8 is calleda vector file or “image packet.”

Other well-known transformation methods such as wavelet analysis mayadditionally or alternatively be utilized to render the image data. Someexamples of wavelet transforms and their use in image storage andanalysis are described in detail in U.S. Pat. No. 5,710,835, thedescription of which is herein incorporated by reference.

These techniques take advantage of grain patterns of wood, which likehuman fingerprints are unique to each individual. In accordance withprocess blocks 128 a and 128 b, additional imaging, filtering, andanalytical techniques can also be employed for identifying repeating ornon-repeating features of each piece of wood 8 and/or modifying imagepacket for the purpose of characterizing and later identifying a pieceof wood 8. These include any characteristics captured or analyzed by theautomated processing system or characteristics scanned and analyzed asdisclosed in any one of U.S. Pat. Nos. 6,757,058; 6,756,789; 5,703,960;5,644,392; 5,524,771; 5,412,220; 5,254,859; 5,252,836; 4,992,949;4,926,350; 4,916,629; 4,879,752; 4,867,213; 4,831,545; 4,827,142;4,606,654; 4,301,373; 4,286,880; 4,221,974; 4,207,472; 4,086,496; orcombinations thereof.

In accordance with process blocks 116 and 118, the image packets aresent to the automated processing system and associated with a wood piecenumber and sent to the computer 20 that will later perform theidentification comparison. In some particular embodiments, the imagepackets may be save in a first-in/first-out (FIFO) packet queue beforethey are associated with a wood piece number as indicated in processblock 130. The interim solution communication involves the destinationand application(s) for the image data once it has been transformed to animage packet. Typically, an image packet's destination will bedetermined by which station 12 or 42 collected the image. If the imagedata is collected by a station 12 and an initial characterization imagepacket is created, a sequential wood piece number (WPN) or code isassigned to the image packet, and the information is sent to a computer20 in communication with a downstream station 42 via the Ethernetconnection in accordance with process block 116. In accordance withprocess block 118, the wood piece number is also made available to theautomated processing system so it can relate the wood piece number toits own information about the piece of wood 8. Alternatively, skilledpersons will appreciate that the wood piece number could be generated bythe automated processing system and communicated to station 12.

In accordance with decision block 140, the computer 20 associated withstation 42 waits to receive the characterization image packet and maystore it in a buffer memory in a sequential queue of image packets asindicated in process block 142 to associate it with a wood piece number.In a particular embodiment with reference to FIG. 3, the software at oneof the computers 20 waits to receive a wood piece number from theautomated processing system in accordance with decision block 150 andsaves the wood piece number in a first-in/first-out queue in accordancewith process block 152. In accordance with a decision block 154, thesoftware then checks whether a reset has been received from theautomated processing system or an operator keyboard. If a reset has beenreceived, then the wood piece number first-in/first-out queue may bereset to zero in accordance with process block 156. If no wood piecenumber reset is indicated, then the software checks for an image packetreset from the automated processing system or an operator keyboard asindicated in decision block 158. If a reset is indicated, then the imagepacket queue may be rest to zero as indicated in process block 160. Ifno rest is indicated, then the software checks to determine whether animage packet is available in accordance with decision block 162.

If an image packet is available, the software confirms in accordancewith decision block 164 that a valid wood piece number is available, andif so, the software assigns the wood piece number from process block 152to the image packet from process block 130 in accordance with processblock 166. The software also transmits the wood piece number to theautomated process system and increments the wood piece number queue.Finally, in accordance with process block 168, the software transmitsthe wood piece number and the image packet to the computer 20 at station42 and increments the image packet queue.

If the image packet is collected at station 42 and a downstream oridentification image packet is created, the software proceeds withwoodprint matching in accordance with process block 144. In oneembodiment, the software at a downstream computer checks to determinewhether a wood piece number and image packet have been received fromstation 12 in accordance with decision block 170 and saves this data toa first-in/first out packet queue in accordance with process block 172.Then the software checks for a reset from the automated processingsystem of an operator keyboard in accordance with process block 174. Areset is performed if indicated in accordance with process block 176, orthe upstream characterization image packet is compared to a downstreamidentification packet as described later in greater detail.

The downstream image packet is then compared to the availablecharacterization image packets in memory to find a match. The wood piecenumber and its location in memory allow the software to search forwardand backward in a logical fashion to look for the image packets ofpieces of wood 8 where they are most likely to be, and then widen so asto find those that have moved out of order. Initial image packetsconcerning pieces of wood 8 whose identities have already been confirmedby the downstream station 42 can be tagged accordingly or discarded sothey do not have to be compared. The matching comparison preferably usesa weighted statistical method to compare a downstream image packet toinitial image packets in memory. Typically two or more data values foreach cell of an image are compared to corresponding data values of cellsin an image packet in memory to look for the numbers to match within apredetermined tolerance. If enough matches are successful for aspecified number of cells, a successful piece of wood identity isassumed. If there are not enough matches, then the next image packet inmemory is considered. This process continues until a match is found, atime limit is reached, or the availability of untested initial imagepackets is exhausted.

In one embodiment, the comparison process may be driven by the expectedflow of wood pieces 8. If the wood pieces 8 are expected to stay inorder as they travel from one station 12 to one station 42, then it maybe reasonable to only confirm that the wood piece 8 arriving at theidentification station 42 is the expected wood piece 8. In a rudimentaryembodiment, a simple accept/reject decision might be sufficient and maybe obtained by thresholding the results, and a reject result might besent directly to the automated processing system in accordance withprocess block 184 a and/or examination or intervention by an operatormight be requested.

An exemplary image packet comparison technique described below employs acell-by-cell comparison scheme that awards points in accordance with thecell test results. The grain direction number from a specific cellderived from the image taken at station 12 is compared to thecorresponding cell derived from the image taken at station 42. If thenumbers match within a very tight tolerance, such as ±1 or up to ±5,then 3 points are awarded for the test, for example. If they matchwithin a wider tolerance, such as +6-10, then 2 points are awarded, forexample, etc. The numbers representing the magnitudes of the spatialfrequencies or other wood piece characteristics can be similarlyevaluated.

If multiple tests, such as for grain direction and frequency magnitude,for a cell achieve 2 or more points, for example, an additional pointcan be awarded to the cell score. Furthermore, if adjacent cell scoresare high, an additional point can be added to the cell score. If thenumber or vector values of individual cells are low because the originalimage had very little grain contrast or the imaged area was veryirregular, the scores for these cells could also be increased toincrease their importance. The total cell scores for each image packetcan then be normalized to a 100% scale. The host computer 20 uses thenormalized test cell scores to determine if the piece of wood 8 isindeed the same piece of wood seen at both stations 12 and 42. In oneembodiment, the normalized test cell scores are converted to an overallconfidence level for the piece of wood 8 being identified, and suchconfidence level may also be affected by the confidence level of thepieces of wood 8 that surround the piece of wood being identified.

In more advanced embodiments, the process may be designed toautomatically recover from a problem. For example, if the identificationimage packet of the wood piece 8 undergoing identification does notpresent a high confidence match to the image packet of the expected woodpiece 8, then the software may check for the presence of additionalimage packets in accordance with decision block 186, and an image packetfor an opposite or other surface of the expected wood piece 8 may becompared to the identification image packet. If a high confidence matchis still not found, then it is possible that the piece of wood 8 mayhave gotten out of position by trading places with its neighbor. Thenthe software may check for the presence of additional image packets inaccordance with decision block 186, so a comparison can be done betweenthe expected wood piece's image packet and its neighbor's imagepacket(s). These multiple-comparison results could be then furthercompared using probability techniques well known to skilledpractitioners to compensate for process particulars. For example, thesoftware may look for and react to changes in confidence level patterns.

Skilled persons will appreciate that each piece of wood 8 may beassociated with two or more image packets if separate packets aredesired for each opposite surface or for each face, side, and/or endsurface or that each piece of wood 8 may be associated with a singleimage packet containing characteristic image data for some or all of thewood's surfaces for which an image is collected. The additional imagepackets associated with each piece of wood 8 can be used for comparisonbefore the image packets concerning other pieces of wood 8 are comparedto allow for possibilities of a piece of wood being turned over in itstravel between stations 12 and 42. Skilled persons will appreciate thatinitial and downstream image packets may include data from one or moreentire surfaces of a piece of wood 8 or from only portions of one ormore surfaces. In some embodiments, stations 12 convert larger portionsof wood piece surface images into image packets and stations 42 convertsmaller portions of wood piece surface images a into image packets.Preferred minimum areas converted into image packets should havesufficient size to reduce inaccurate identifications.

Once a match is, or is not, found, in accordance with decision blocks180 a and 180 b, the final solution communication involves making theinformation available to the automated process system. A successfulmatch is signaled by presenting the matching sequential board number tothe automated processing system via Ethernet connection in accordancewith process blocks 182 a and 182 b. A non-match is communicated bypresenting a specific failure code in accordance with process blocks 184a and 184 b. Additional algorithms can be used to complement thosedescribed. Some wood piece surfaces will be darker or offer lesscontrast. Sometimes these can be enhanced using additional filteringmethods. It may be desirable to modify the image processing algorithmsby adding other filtering techniques in order to make the system morerobust to accommodate such variables. Additional camera types and imageacquisition hardware configurations at both stations 12 and 42 can beimplemented along with modifications for processing the image data.

For example, if the data collected by the image acquisition hardware 16is presented to the computer 20 or its image collection hardware 18 in amanner inconsistent with existing equipment and processing software, theimage processing software can be adapted to integrate with it. Ascomputers continue to evolve, there will be more options available forimage processing, communication, and other software tasks. Skilledpersons will appreciate that the software will evolve with the computerplatform hardware as the resulting architecture or speed and memoryenhancements make other software techniques favorable.

In some embodiments, all or major portions of the image processingsoftware reside in a single computer 20. In other embodiments, all ormajor portions of the image processing software reside in each computer20. In yet other embodiments, specific image processing tasks may beallocated to specific computers 20 or spread out over multiple computers20. In a further embodiment, some computers 20 may contain all or majorportions of the image processing software while other computers 20 mayperform only minor tasks. Another specific example includes taking theimage acquisition and processing tasks that would be done in station 12and integrating them into a scanning system that acquires wood pieceimages for other purposes. The scanning system would produce the imagepacket information along with its own tasks and either keep suchinformation for later comparison to the downstream identificationimages, or pass the image packets along to station 42 with a sequentialwood piece number.

In systems with a single computer 20, the image acquisition hardware 16from both stations 12 and 42 are connected directly or indirectly to thecomputer 20 and processed with the image processing software installedon the computer 20. This computer 20 would also be connected to theproduction equipment and possibly other computers 20. Additional cablingconfigurations are possible that connect the computer 20 with a separateimage collection/processing system.

In addition, preferred embodiments employ quality control componentsthat can be incorporated into or communicate with pre-existing activeself-checking capabilities of existing systems, such that if the systemfails, very few boards could pass before a problem is discovered.

An exemplary application of the board print™ technology is describedbelow in the context of a system used to automatically grade wood pieces8 in a planer mill. The wood pieces 8 are graded boards that vary inthickness and width from 2.5×10 centimeters to 5×30 centimeters (1×4inches to 2×12 inches) and vary in length from 2.4 to 6 meters (8 to 20feet) long. The boards are kiln dried and pass through a grading systemduring the planning, trimming, and sorting process. The boards travelthrough a planer at lineal speeds averaging 47 meters/minute (1800feet/min.), immediately pass through the grading scanner, and land on adeck from where chains transport the boards as they are oriented in atransverse direction. At this stage in the process, the boards are notcompletely controlled, and do not necessarily stay in queue. After a fewseconds, the boards are physically separated into individual sections ona lugged chain. It is then desirable to match a board identity with theinformation collected at the grading scanner because the board will nextbe trimmed and sorted into a package by automated equipment.Accordingly, a station 42 is preferably located at a position whereboards can be identified before they are trimmed and sorted.

When a board passes through the grading scanner, several small halogenlamps and line scan cameras collect image data for the top and bottomwide faces 30 of the board. The data is collected by one or more of aset of computers 20 containing hardware and software for controlling theacquisition and data collection process, and the board is assigned asequential board number. The primary use of the image data is forgrading the board, however, a portion of the image data is alsoprocessed in the computer 20 for its board print™ information. Thismeans that the data be warped for size and orientation, FFT values willbe generated, the resulting data will be adjusted to compensate forbrightness; and the data will be placed in the vector image packet. Theimage packet is then sent to a host computer 20 where it is stored forthe matching process later. This image packet contains information forboth the top and bottom wide faces 30 of the board, plus the sequentialboard number. The sequence number and image data for this board is sentto one of the computers 20, each computer 20 preferably containing thesame hardware and software dedicated to image processing. The next boardthat is scanned will be assigned the next number in sequence and itsimage data is passed to another one of the computers 20.

After the board finally gets singulated onto the lugged chain, theautomatic processing system controlling the production line activates acamera at the identification station 42 and an image is acquired of thetop face 30 of the board, which may be oriented transversely to thedirection of travel 6. The camera sends the image data via Fire Wireserial format to an external conversion device where the signal isconverted to a fiber optic medium and sent to a dedicated board print™computer 20. When it arrives at the computer 20, external hardwareconverts the data back to Fire Wire serial format and stores theinformation in a circular buffer. Software in the computer 20 pulls itout of the buffer and processes it as previously described with anadditional step of reorienting the image. Then, the computer 20 relaysthe data to the host computer 20 via an Ethernet connection for thecomparison as previously described.

The host computer 20 compares the vector image packet just received fromthe station 42 with the image packets from eleven boards for example,such as five boards in the queue ahead of this board, and five boardsafter this board. Comparison steps are employed as previously describedexcept as modified by the specific embodiment hereinafter described.

Once the comparison scores are generated, the host computer 20 performsthe following tasks. If the board score for the expected match is equalor higher than the scores for the adjacent boards, it is considered amatch. If the board score for the expected match is up to 20% lower thanthe scores for any adjacent boards, then the board is considered amatch. However, a probability weighting may require that the next boardhave at least a 10% higher score than that of adjacent boards or berejected. If the board score for the expected match is more than 20%lower than scores for the adjacent boards, the board is rejected. Oncethree boards are rejected in a row, the program will automaticallyadjust to realign the queue. The software does this using data from thelast three board comparisons to determine whether there is a trend forone specific board position that is higher than or equal to the scoresfor adjacent boards as described above. If no trend can be detected inthe ten adjacent positions, the host computer 20 instructs the automaticprocessing system to stop the material flow so the boards can bemanually sorted by an operator.

Once an identity decision is made, the host computer 20 transmits thecorresponding sequential number and relevant process information (gradeand trim decision) to the automatic processing system so it can trim andsort the board accordingly.

In yet another embodiment, a grading system or the automated processingsystem determines a cutting solution for the pieces of wood 8 thatrecommends the they be cut into multiple smaller pieces of wood. Theimage characterization system collects or sorts image data such that animage packet is created for each of the forecast smaller pieces. Skilledperson will appreciate that some embodiments may not provide imagepackets for forecast pieces of wood 8 resulting from internal cuts. Anidentification station can creates image packets for the recommendedmultiple smaller pieces of wood after they are cut to confirm theidentify of some or all of them.

Skilled persons will appreciate that variations in size, materials,shape, form, function, manner of operation, assembly, and use may impactoptimum dimensional and positioning relationships, hardware components,software applications, and system connectivity.

It will be obvious to those having skill in the art that many changesmay be made to the details of the above-described embodiments withoutdeparting from the underlying principles of the invention. The scope ofthe present invention should, therefore, be determined only by thefollowing claims.

1. A method for tracking multiple pieces of wood in a wood processingsystem, comprising: obtaining inherent wood characteristic informationfrom first and second pieces of wood at a first station; and using theinherent wood characteristic information obtained at the first stationto confirm the identify of the first and second pieces of wood at asecond station.
 2. The method of claim 1 in which the first and secondpieces of wood each have a surface and the inherent wood characteristicinformation is obtained from the surface.
 3. The method of claim 1 inwhich the first and second pieces of wood each have at least first andsecond surfaces and the inherent wood characteristic information isobtained from both the first and second surfaces.
 4. The method of claim1 in which obtaining the wood surface characteristic information furthercomprises obtaining an image of at least a portion of the first andsecond pieces of wood.
 5. The method of claim 1 in which the woodsurface characteristic information comprises a grain characteristic. 6.The method of claim 5 in which the grain characteristic comprises grainfrequency magnitude, grain direction, and/or grain direction confidence.7. The method of claim 1 in which the wood surface characteristicinformation comprises tracheid data.
 8. The method of claim 1 in whichthe first and second pieces of wood comprise at least one of thefollowing: timber, lumber, log, flitch, cant, beam, post, stud, orboard.
 9. The method of claim 1 in which the first and second pieces ofwood are surfaced or unsurfaced.
 10. The method of claim 1 in which thefirst and second pieces of wood comprise any level of moisture contentwithin the range of uncured to cured.
 11. The method of claim 1 in whichthe first and second pieces of wood each comprise a board and theinherent wood characteristic information comprises a defect.
 12. Themethod of claim 11 in which the defect comprises at least one of bark,missing wood, or a physical shape defect.
 13. The method of claim 12 inwhich the physical shape defect comprises a wane defect.
 14. The methodof claim 1 in which the first and second pieces of wood each comprise aboard and the inherent wood characteristic information is obtained froman end, side, or face of the board.
 15. The method of claim 1 in furthercomprising employing a camera to obtain the inherent wood characteristicinformation.
 16. The method of claim 1 in further comprising employing aphotodiode to obtaining the inherent wood characteristic information.17. The method of claim 1 in further comprising employing an antenna toobtain the inherent wood characteristic information.
 18. The method ofclaim 1 further comprising employing a light source to illuminate thepieces of wood as their inherent wood characteristic information isobtained.
 19. The method of claim 18 in which the light source is pulsedor strobed.
 20. The method of claim 18 in which the light sourcepresents a light line.
 21. The method of claim 18 in which the lightsource emits at least a green wavelength.
 22. The method of claim 1further comprising exposing the pieces of wood to x-ray radiation tofacilitate obtaining their inherent wood characteristic information. 23.The method of claim 1 further comprising exposing the pieces of wood toradio waves to facilitate obtaining their inherent wood characteristicinformation.
 24. The method of claim 1 in which the wood surfacecharacteristic information is obtained in cooperation with a woodgrading system.
 25. The method of claim 1 in which the inherent woodcharacteristic information is obtained from a wood surface of anintended appearance-grade product.
 26. The method of claim 1 in whichthe inherent wood characteristic information provides for each of thefirst and second pieces unique identification data without contactingthe first or second pieces of wood.
 27. The method of claim 3 in whichthe inherent wood characteristic information of only either one of thefirst or second surfaces of the piece of wood is obtained at the secondstation to uniquely identify the piece of wood.
 28. The method of claim1 further comprising: obtaining inherent wood characteristic informationfrom first, second, and third pieces of wood in consecutive order; andusing the inherent wood characteristic information obtained at the firststation to uniquely identify the first, second, and third pieces of woodat the second station regardless of the order in which they arrive atthe second station.
 29. The method of claim 1 in which confirming theidentity of the first and second pieces of wood further comprises:obtaining inherent wood surface characteristic information from at leasta portion of the first and second pieces of wood at the second station;and comparing at least a portion of the wood surface characteristicinformation obtained at the second station for the first piece of woodagainst the wood surface characteristic information of the respectiveportions of one or both of the first and second pieces of wood toidentify a match within predetermined statistical parameters.
 30. Themethod of claim 29 in which the comparisons are performed by a centralcomputer.
 31. The method of claim 30 in which the comparisons areperformed by a computer associated with the second station.
 32. Themethod of claim 29 in which obtaining inherent wood characteristicinformation further comprises: obtaining an image from a portion ofrespective surfaces of the first and second pieces of wood at bothstations; and independently adjusting images of the respective surfacesof the first and second pieces of wood at both stations to conform to apredetermined size and orientation.
 33. The method of claim 32, furthercomprising: characterizing the images with a Fast Fourier Transformationtechnique.
 34. The method of claim 32, further comprising: dividing eachimage into a corresponding array of image portion cells; characterizingthe inherent wood characteristic information within the image portioncells with a Fast Fourier Transformation technique to provide for someor all of the cells at least one value for the inherent woodcharacteristic information; and comparing the values of correspondingcells of respective images to determine whether a sufficient number ofcorresponding cells have sufficiently similar values to be presented asa match or sufficiently different values to be presented as a nonmatch.35. The method of claim 1 further comprising: cutting the first piece ofwood into at least third and fourth pieces of wood; and using theinherent wood characteristic information obtained at the first stationto confirm the identify of at least the third or the fourth pieces ofwood.
 36. The method of claim 1 in which a cutting solution isdetermined for the first piece of wood that recommends the first pieceof wood be cut into multiple smaller pieces of wood and in whichinherent wood characteristic information is obtained for some of therecommended multiple smaller pieces of wood, further comprising: cuttingthe first piece of wood into at least third and fourth pieces of wood;and using the inherent wood characteristic information obtained at thefirst station to confirm the identify of some of the recommendedmultiple smaller pieces of wood.
 37. A wood tracking system, comprising:first image acquisition hardware for collecting a first image of atleast a first portion of a surface of a piece of wood as it travelsacross a first image collection area; second image acquisition hardwarefor collecting a second image of at least a second portion of thesurface of the piece of wood as it travels across a second imagecollection area at a different location than the first image collectionarea, the second portion including some or all of the first portion;image processing software located on one or more computers forindependently adjusting first and second portions of respective firstand second images to conform to a predetermined size and orientation;image characterization software located on one or more computers forindependently characterizing an inherent wood surface characteristicappearing in the first and second portions of the respective first andsecond images to independently create values for the inherent woodsurface characteristics within the respective first and second imageportions; and image comparison software located on one or more computersfor comparing the values of the inherent wood surface characteristicswithin the respective first and second image portions and fordetermining whether the values have sufficient similarities to bepresented as a match or sufficient differences to be presented as anonmatch.
 38. The wood tracking system of claim 37 in which multiplepieces of wood travel across the first and second image collectionareas, each piece of wood has at least first and second surfaces, andimages are obtained from both the first and second surfaces of eachpiece of wood in proximity to at least one of the image collectionareas.
 39. The wood tracking system of claim 37 in which the inherentwood surface characteristic comprises a grain characteristic value. 40.The wood tracking system of claim 39 in which the grain characteristicvalue comprises grain frequency, grain frequency magnitude, graindirection, contrast, and/or grain direction confidence.
 41. The woodtracking system of claim 37 in which the inherent wood surfacecharacteristic comprises tracheid data.
 42. The wood tracking system ofclaim 37 in which multiple pieces of wood travel across the first andsecond image collection areas and the pieces of wood comprise at leastone of the following: timber, lumber, log, flitch, cant, beam, post,stud, board, or veneer.
 43. The wood tracking system of claim 37 inwhich multiple pieces of wood travel across the first and second imagecollection areas and the pieces of wood comprise any level of moisturecontent within the range of cured to uncured.
 44. The wood trackingsystem of claim 37 in which multiple pieces of wood travel across thefirst and second image collection areas and the pieces of wood compriseany level of moisture content.
 45. The wood tracking system of claim 37in which multiple pieces of wood travel across the first and secondimage collection areas and in which the pieces of wood each comprise aboard and the inherent wood surface characteristic comprises a defectincluding one of the following: bark, missing wood, or a twist.
 46. Thewood tracking system of claim 37 in which multiple pieces of wood travelacross the first and second image collection areas and in which thepieces of wood each comprise a board and the inherent wood surfacecharacteristic is obtained from an end, side, or face of the board. 47.The wood tracking system of claim 37 in which the first and/or secondimage acquisition hardware comprises a camera.
 48. The wood trackingsystem of claim 38 further comprising first and second light sources atthe respective first and second image collection areas for illuminatingthe surface of the piece of wood.
 49. The wood tracking system of claim48 in which the light source presents a light line.
 50. The woodtracking system of claim 48 in which the light source emits at least agreen wavelength.
 51. The wood tracking system of claim 37 in which theinherent wood surface characteristic is obtained in cooperation with awood grading system.
 52. The wood tracking system of claim 37 in whichthe inherent wood surface characteristic is obtained from a wood surfaceof an intended appearance-grade product.
 53. The wood tracking system ofclaim 37 in which the inherent wood surface characteristic providesunique identification data without contacting the first or second piecesof wood.
 54. The wood tracking system of claim 37 in which the woodsurface characteristic information of only either one of the first orsecond sides of the piece of wood is employed at the second station touniquely identify the piece of wood.
 55. The wood tracking system ofclaim 37 in which the image characterization software employs FastFourier Transformation or wavelet analysis.
 56. The wood tracking systemof claim 37 in which the image acquisition hardware collects radiofrequency data.
 57. The wood tracking system of claim 37 in which theimage processing software, image characterization software, and imagecomparison software are all located on one computer.
 58. The woodtracking system of claim 37 in which at least one of the imageprocessing software, image characterization software, or imagecomparison software is located on a computer that is remote from atleast one of the image collection areas.
 59. The wood tracking system ofclaim 37 further comprising: a cutting station for cutting the piece ofwood into at least second and third pieces of wood such that the secondportion of the wood piece surface is located on the second or thirdpieces of wood.
 60. The wood tracking system of claim 37 in which acutting solution is determined for the piece of wood that recommends thepiece of wood be cut into multiple smaller pieces of wood and in whichinherent wood surface characteristics are characterized for some of therecommended multiple smaller pieces of wood, further comprising: acutting station for cutting the piece of wood into the recommendedmultiple smaller pieces of wood such that a first image are obtainedfrom some of the recommended multiple smaller pieces of wood before thepiece of wood is cut and such that second images are obtained from someof the recommended multiple smaller pieces of wood after they are cut toconfirm the identify of some of the recommended multiple smaller piecesof wood.
 61. A method for characterizing a piece of wood, comprising:capturing an image of at least a portion of at least one surface of apiece of wood; creating from the image an image packet of dataconcerning inherent characteristics of the piece of wood and thatuniquely identifies the piece of wood; and using the image packet toconfirm the identity of the piece of wood.
 62. A substantially automatedwood processing system, comprising: a wood evaluation station foracquiring data about numerous inherent characteristics of a piece ofwood, the wood evaluation station adapted for using at least some of thedata to create a first vector packet of data that uniquely identifiesthe piece of wood; and a wood identification station for acquiring dataabout at least one of the numerous inherent characteristics of the pieceof wood to create a second vector packet of data that can be compared tothe first vector packet of data to confirm the identity of the piece ofwood.
 63. A wood identification system for acquiring data about at leastone of numerous inherent characteristics of a piece of wood, comprising:image acquisition hardware for collecting image data concerning inherentcharacteristics from at least a portion of a piece of wood; image datacharacterization software for creating from the image data averification image packet concerning inherent characteristics of thepiece of wood and that uniquely identifies the piece of wood; and imagecomparison software for comparing the verification image packet to anidentification image packet derived from image data collected by a woodcharacterization system that evaluates inherent characteristics of thepiece of wood and for determining whether the verification andidentification image packets have sufficient similarities to bepresented as a match or sufficient differences to be presented as anonmatch.